JSM 2015 Online Program

Online Program Home
My Program

Abstract Details

Activity Number: 190
Type: Contributed
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract #317602
Title: Statistical Properties of Convex Clustering
Author(s): Kean Ming Tan* and Daniela Witten
Companies: University of Washington and University of Washington
Keywords: single linkage clustering ; convex clustering ; degrees of freedom ; fusion penalty ; hierarchical clustering ; prediction error

In this paper, we study the statistical properties of convex clustering. Through its dual problem, we establish that convex clustering is closely related to single linkage clustering. In addition, we derive the range of the tuning parameter for convex clustering that yields a non-trivial solution. We also provide an unbiased estimate of the degrees of freedom, and provide a finite sample bound for the prediction error for convex clustering. We compare convex clustering to some traditional clustering methods in a simulation study.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program

For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home